pyproject.toml

[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"

[project]
name = "spooky"
version = "0.1.0"
description = "Hybrid quantum-classical multi-robot path planning using QUBO formulations"
authors = [
    {name="JavideuS", email="javi.rm2005@gmail.com"}
]
readme = "README.md"
license = {text = "Apache-2.0"}
requires-python = ">=3.8"
keywords = [
    "path planning",
    "multi-robot",
    "QUBO",
    "quantum annealing",
    "QAOA",
    "robotics",
    "quantum computing"
]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Science/Research",
    "Intended Audience :: Developers",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.12",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Topic :: Scientific/Engineering :: Physics",
    "Topic :: Software Development :: Libraries :: Python Modules",
]
dependencies = [
    "pyyaml",
    "h5py",
    "numpy",
    "pennylane",
    "networkx", # Used by the CBS classical baseline
]

[project.optional-dependencies]
gpu = [
    "custatevec-cu12",
    "pennylane-lightning-gpu",
]
dwave = [
    "dimod",
    "dwave-system",
    "dwave-neal",
]
ibm = [
    "qiskit-ibm-runtime",
    "pennylane-qiskit",
]
ros = [
    "pillow",
]
iqm = [
    # qrisp[iqm] pulls in iqm-client and provides qrisp.interface.IQMBackend,
    # the execution path Pennylane_solver.py bridges into for real IQM hardware
    # (PennyLane -> Qiskit -> Qrisp) — see Pennylane_solver.py's IQM comments
    # for why qiskit.remote's Sampler can't be used directly against IQM.
    "qrisp[iqm]",
    "pennylane-qiskit",
    "python-dotenv",
]
jupyter = [
    "ipykernel",
    "nbformat>=4.2.0",
]
dev = [
    "pytest",
    "black",
    "flake8",
]

visualizer = [
    "plotly",
    "kaleido",
]

fastapi = [
    "fastapi",
    "uvicorn",
    "python-multipart",  # required by FastAPI's UploadFile form parsing
    "dash",
]

paper = [
    "matplotlib",
]

classical = [
    "pyomo",
    "highspy",
]

# quantum/benchmark/sweep_runner.py + quantum/benchmark/analysis/
benchmark = [
    "pandas",
    "scipy",
]

all = [
    "spooky[gpu,dwave,ibm,iqm,jupyter,dev,visualizer,fastapi,paper,ros,classical,benchmark]",
]

# PennyLane ships no CUDA/lightning-gpu wheels for Windows, so this mirrors
# "all" minus the gpu extra.
windows = [
    "spooky[dwave,ibm,iqm,jupyter,dev,visualizer,fastapi,paper,ros,classical,benchmark]",
]

[project.urls]
Homepage = "https://github.com/JavideuS/Spooky"
Repository = "https://github.com/JavideuS/Spooky"
Issues = "https://github.com/JavideuS/Spooky/issues"

[project.scripts]
spooky-solve = "quantum.qubo_cli:main"
spooky-sweep = "quantum.benchmark.run_sweep:main"

[tool.setuptools.packages.find]
where = ["."]
include = ["quantum*"]
exclude = ["quantum.prueba*", "quantum.tfg_proves*", "quantum.paper*"]

# Data the library loads at runtime relative to its own __file__, so it has to
# travel with the package. Without this a non-editable `pip install .` copies
# only the .py files. Map .h5 files are deliberately NOT listed here — they're
# generated artifacts (see maps/yaml2HDF5.py); the 1000x1000 map alone is 11MB,
# so bundling every .h5 would balloon the wheel. registry.py generates missing
# .h5 files on demand from the bundled .yaml sources instead, cached outside
# the install so it survives on a read-only or reinstalled package dir.
# "images/*.png" is the only extension the visualizer's default "auto" theme
# actually loads (quantum/images/*.jpg and *.svg are unused leftovers).
[tool.setuptools.package-data]
"quantum" = ["images/*.png"]
"quantum.config" = ["*.yaml"]
"quantum.maps" = ["*.yaml"]